如何從 Apple Podcasts 建立播客聯絡名單：排行榜、節目集數與聯絡電郵

How to Build a Podcast Outreach List from Apple Podcasts

Getting booked as a podcast guest, or finding shows to sponsor, is mostly list-building: find relevant shows, check they're active, find who to contact. Paid podcast databases do this for a monthly fee. You can do most of it yourself with public data: Apple's iTunes Search API and each podcast's own RSS feed.

This tutorial explains where the data comes from and uses the Apple Podcasts Scraper to turn it into a spreadsheet.

Where the data comes from

1. iTunes Search API (official, free): search podcasts by keyword, look up shows by ID. Gives title, author, genres, episode count, last release date, artwork and the RSS feed URL.
2. Apple Marketing Tools RSS: Top Podcasts charts by country.
3. The show's RSS feed (published by the podcaster): description, website, episodes, and often an itunes:owner block with a name and email that the publisher chose to make public.

That last point matters. The email isn't scraped from a website or guessed; it's the contact the podcaster put in their own public feed for directories. Not every show includes one.

Step 1: Search a niche

Open the actor and click Try for free. It's prefilled with the search term marketing and 10 results. Start it:

Each podcast row also has lastReleaseDate, feedUrl, appleUrl, websiteUrl, ownerName, genres, explicit and language.

Add more search terms, one per line (SaaS, bootstrapping, B2B sales), and raise maxResultsPerSearch.

Step 2: Charts and specific shows

• includeTopChart + country + chartSize: export Apple's Top Podcasts chart for a country, with chartRank.
• podcastIds: look up specific shows by ID or Apple URL, e.g. https://podcasts.apple.com/us/podcast/the-daily/id1200361736.
• maxEpisodesPerPodcast: also export recent episodes (title, date, duration, description) from the RSS feed.

Step 3: Filter to active, reachable shows

from apify_client import ApifyClient
import datetime

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("scrape-smith/apple-podcasts-scraper").call(run_input={
    "searchTerms": ["saas", "bootstrapping", "indie hackers"],
    "maxResultsPerSearch": 50,
    "includeRssDetails": True,
})
cutoff = (datetime.datetime.utcnow() - datetime.timedelta(days=30)).isoformat()
seen, shortlist = set(), []
for p in client.dataset(run["defaultDatasetId"]).iterate_items():
    if p.get("type") != "podcast" or p["podcastId"] in seen:
        continue
    seen.add(p["podcastId"])
    if p.get("ownerEmail") and (p.get("lastReleaseDate") or "") > cutoff:
        shortlist.append(p)
for p in shortlist:
    print(p["title"], "|", p["episodeCount"], "eps |", p["ownerEmail"])

This keeps only shows that published in the last 30 days and list a contact, the two things that matter most for outreach.

Outreach etiquette

A list is not permission to spam. Personalise every email (reference a specific episode; that's what maxEpisodesPerPodcast is for), keep it short, and respect anti-spam rules like CAN-SPAM and GDPR. Hosts get a lot of generic pitches. The ones that work show you actually listened.

Use cases

• Guest booking for founders, authors and consultants.
• Sponsorship and ad buying research.
• Chart tracking by country over time.
• Market research: how crowded is a niche, how often do shows publish.
• Episode datasets for AI summaries or search.

Honest limitations

• ownerEmail only exists if the publisher put it in their feed. Expect a mix.
• Apple asks for about 20 API calls per minute, and the actor respects that, so large searches take a few minutes.
• Search ranking is Apple's; you'll see the same shows Apple shows.
• Not affiliated with Apple. Data belongs to Apple and the respective publishers.

Cost

$0.002 per podcast (including the RSS details and email lookup) and $0.0003 per episode. The 10-show test is two cents; 500 shows is $1; 5,000 episodes is $1.50.

Wrap-up

With public APIs and a bit of filtering, you can build a better-targeted outreach list than many paid databases. Try the Apple Podcasts Scraper with the prefilled search, then plug in your niche.

Scrape-Smith builds small, cheap data tools on public and official APIs.